5 #ifndef ROOT_TMVA_VariableImportance 6 #define ROOT_TMVA_VariableImportance void SetType(VIType type)
TH1F * GetImportanceHist()
virtual void Evaluate()
Virtual method to be implemented with your algorithm.
OptionMap fImportanceValues
class to storage options for the differents methods
~VariableImportanceResult()
1-D histogram with a float per channel (see TH1 documentation)}
std::shared_ptr< TH1F > fImportanceHist
TCanvas * Draw(const TString name="VariableImportance") const
#define ClassDef(name, id)
std::unique_ptr< Factory > fClassifier
Abstract base class for all high level ml algorithms, you can book ml methods like BDT...
const VariableImportanceResult & GetResults() const
VariableImportance(DataLoader *loader)
void EvaluateImportanceShort()
TH1F * GetImportance(const UInt_t nbits, std::vector< Float_t > &importances, std::vector< TString > &varNames)
OptionMap & GetImportanceValues()
Abstract ClassifierFactory template that handles arbitrary types.
VariableImportanceResult()
VariableImportanceResult fResults
void EvaluateImportanceAll()
void EvaluateImportanceRandom(UInt_t nseeds)